Bibliographic record
Abstract
Sjögren syndrome (SS) is a chronic inflammatory autoimmune disease that primarily affects the lacrimal and salivary glands. Glandular tissue destruction progresses with disease progression, severely impairing the patient’s quality of life. The disease is not limited to the glandular tissue alone, with a high risk of various extraglandular manifestations and malignant lymphomas.1,2 Nearly a century after Dr. Henrik Sjögren’s report in 1933, SS has seemingly reached a significant turning point.3 In recent years, several editorials have suggested redefining SS as Sjögren disease and eliminating the distinction between the primary and secondary forms; similar opinions were raised by SS patient groups at the 15th International Symposium on Sjögren’s in 2022.4,5 In addition, the classical idea that SS affects middle-aged women is certainly overdue for a revision, especially now that childhood SS is receiving increasing attention.6 However, most cases of childhood SS do not meet the 2016 American College of Rheumatology/European Alliance of Associations for Rheumatology (ACR/EULAR) criteria, which are the most recent classification criteria for SS.7-9 This may be because imaging examinations have not been included in the classification criteria since the publication of the 2012 ACR criteria.10 Since the publication of the 2012 ACR criteria, reports on the usefulness of imaging examinations in diagnosing SS have increased substantially. Salivary gland ultrasonography (US) has contributed to this trend. US was first used to diagnose SS in the late 1980s, and … Address correspondence to Assoc. Prof. Y. Takagi, Department of Radiology and Biomedical Informatics, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1, Sakamoto, Nagasaki 852-8588, Japan. E-mail: yuki{at}nagasaki-u.ac.jp.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.101 | 0.027 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".